CUIDADOS PALIATIVOS E A INTERVENÇÃO DO ASSISTENTE SOCIAL JUNTO ÀS EQUIPES MULTIPROFISSIONAIS

The Palliative Care concept was re-signified from the holistic perspective of health that sees the being in its multidimensions, valuing care with physical, psychological, social, emotional and spiritual well-being, through promotion actions aimed at citizenship. Interdisciplinary action is a prerequisite of Palliative Care and the social worker is one of the professionals who make up the teams. The objective of this work is to understand Palliative Care and the role of social workers in multidisciplinary teams. The investigation was anchored in qualitative research, with a bibliographical approach and sought in the literature subsidies for critical-theoretical reflection. It is concluded that there is a need for recognition of the multidisciplinary work in Palliative Care and appropriation of the social worker to the area, so that he has mastery of the dimensions that make up his work.                                        O conceito Cuidados Paliativos foi ressignificado a partir da perspectiva holística de saúde que enxerga o ser em suas multidimensões, prezando cuidados com o bem-estar físico, psicológico, social, emocional e espiritual, através de ações de promoção que visam à cidadania. A atuação interdisciplinar é pressuposto dos Cuidados Paliativos e o assistente social é um dos profissionais que compõem as equipes. O objetivo deste trabalho é compreender os Cuidados Paliativos e a atuação dos assistentes sociais nas equipes multiprofissionais. A investigação ancorou-se na pesquisa qualitativa, de abordagem bibliográfica e buscou na literatura subsídios para a reflexão crítico-teórica. Conclui-se que há necessidade de reconhecimento do trabalho multiprofissional nos Cuidados Paliativos e apropriação do assistente social à área, para que possua domínio das dimensões que compõem sua atuação

Prevalence of depressive symptoms among pregnant adolescents

Objetivo: verificar sintomas depressivos em gestantes adolescentes em unidade básica de saúde. Métodos: Cinquenta e cinco adolescentes grávidas foram entrevistadas na unidade de saúde. Para a coleta de dados, foram utilizados dois instrumentos: um para dados sociais, demográficos, obstétricos, relações familiares e eventos de violência, e outro para avaliar os sintomas depressivos - Inventário de Depressão de Beck. Resultados: 10,9% das entrevistadas tinham história prévia de depressão ou ansiedade e 3,6% apresentavam um desses problemas no momento da entrevista. 63,6% das adolescentes relataram ter sofrido algum evento estressante no último ano. 49,1% das adolescentes grávidas apresentam sintomas depressivos variando entre leve, moderado e grave. Conclusões: é essencial identificar os primeiros sintomas depressivos em gestantes, para que elas sejam encaminhadas ao serviço especializado, ou detectar a presença de uma equipe de saúde mental em um centro de saúde, para prestar um tratamento adequado e um cuidado de qualidade e humanizado

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Evaluation Of The Quality Of Assistance In An Pre-Hospital Mobile Emergency Service

Background: to evaluate the quality of the assistance of a Mobile Emergency Care Service and to compare the evaluation of professionals according to training and level of education. Methods and Findings: this is a cross-sectional study, with a Donabedian theoretical reference. The sample was all the professionals of a Mobile Emergency Service and data collection performed by a previously validated quality assessment instrument. Some aspects of the service structure were evaluated negatively, and the process was evaluated in a positive way, in general. When comparing the evaluation of quality according to professional category and education, it was verified that the indicators of structure and process were considered appropriate by the professionals of average level and inadequate by the personnel of superior level. Conclusion: the professionals identified flaws in the service structure, which can impact the assistance provided. The level of education influenced the evaluation of the quality of the service. Keywords: Emergency medical services; Health Evaluation; Prehospital care; Evaluation studies; Health services &nbsp